---
name: relationship-design
description: Design AI-first interfaces that build ongoing relationships through memory, trust evolution, and collaborative planning. Use when designing agentic UX, memory-aware interfaces, or relationship-centric product experiences. NOT for general UI/UX tasks.
metadata:
  author: bencium
---

# Agentic UX Design — Relationship-Centric Interfaces

Design framework for AI-first interfaces that build ongoing partnerships, not isolated session interactions.

## Core Shift

Traditional UX optimizes for sessions. Relationship-centric UX optimizes for **sustained partnerships**.

"Every interaction builds on learned preferences and user history. Systems don't just respond — they develop understanding that compounds over time."

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## Five Pillars

### 1. Memory Revolution
Moving beyond static preferences to capture:
- Behavioral patterns across sessions
- Emotional context (frustration, delight, confusion patterns)
- Temporal evolution (how needs change over time)
- Implicit signals (what users skip, ignore, repeat)

Design for: "What would this system know about the user after 3 months?"

### 2. Trust as Design Material

Three-stage trust model:
1. **Transparency** — system shows all reasoning, asks permission
2. **Selective Disclosure** — system explains only when deviating from expectations
3. **Autonomous Action** — system acts independently with clear recovery paths

Design for: trust that can be inspected, corrected, and rebuilt.

### 3. Relationship-Centric Architecture
Maintain continuous awareness of:
- User goals (not just current task)
- Communication patterns (terse vs. exploratory)
- Historical preferences
- Outstanding commitments

Design for: context that doesn't reset between sessions.

### 4. Dynamic Path Planning
Systems that construct workflows aligned with individual objectives:
- "What is this user actually trying to accomplish?"
- Adaptive suggestions based on observed patterns
- Proactive surfacing of relevant information

### 5. New Success Metrics

Replace traditional metrics with:
- **Relationship quality**: does the system understand the user better over time?
- **Compounding value**: does each interaction make future interactions more valuable?
- **Context accuracy**: is stored understanding correct and current?
- **Democratic alignment**: does the system serve the user's actual goals, not engagement goals?

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## Design Process

1. **Understand relationship context** — what ongoing relationship is this product building?
2. **Map trust evolution** — how does trust develop over days, weeks, months?
3. **Design memory architecture** — what should be remembered, forgotten, surfaced?
4. **Build collaborative patterns** — how does the system and user co-create over time?
5. **Define success across timeframes** — week 1, month 1, month 6 metrics

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## Common Pitfalls

- Treating memory as static settings rather than dynamic behavioral understanding
- Using traditional engagement metrics (DAU, session length) for relationship-based systems
- Designing trust as binary (trusted/not) rather than a spectrum
- Building for the first interaction, not the 100th
- Storing everything users say rather than what's actually useful to remember